NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Lai, Mark H. C. – Journal of Educational and Behavioral Statistics, 2019
Previous studies have detailed the consequence of ignoring a level of clustering in multilevel models with straightly hierarchical structures and have proposed methods to adjust for the fixed effect standard errors (SEs). However, in behavioral and social science research, there are usually two or more crossed clustering levels, such as when…
Descriptors: Error of Measurement, Hierarchical Linear Modeling, Least Squares Statistics, Statistical Bias
Peer reviewed Peer reviewed
Direct linkDirect link
VanHoudnos, Nathan M.; Greenhouse, Joel B. – Journal of Educational and Behavioral Statistics, 2016
When cluster randomized experiments are analyzed as if units were independent, test statistics for treatment effects can be anticonservative. Hedges proposed a correction for such tests by scaling them to control their Type I error rate. This article generalizes the Hedges correction from a posttest-only experimental design to more common designs…
Descriptors: Statistical Analysis, Randomized Controlled Trials, Error of Measurement, Scaling
Peer reviewed Peer reviewed
Direct linkDirect link
Sun, Shuyan; Pan, Wei – International Journal of Research & Method in Education, 2014
As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Longitudinal Studies, Educational Research
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Vanhove, Jan – Studies in Second Language Learning and Teaching, 2015
I discuss three common practices that obfuscate or invalidate the statistical analysis of randomized controlled interventions in applied linguistics. These are (a) checking whether randomization produced groups that are balanced on a number of possibly relevant covariates, (b) using repeated measures ANOVA to analyze pretest-posttest designs, and…
Descriptors: Randomized Controlled Trials, Intervention, Applied Linguistics, Statistical Analysis